Software Engineer, Infrastructure
AI in this role
Design and build distributed infrastructure systems powering large-scale AI model training and serving platforms.
The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.
About the RoleWe're hiring a Software Engineer, Infrastructure to design and build the distributed systems that power our model training and serving platforms. You'll work on the systems underlying everything we do — from the clusters that train our frontier models with Inkling, to the multi-tenant serving infrastructure behind Tinker.
This is a foundational infrastructure role at a fast-moving startup. You'll have real ownership over systems that run at large scale, and your work will directly determine how quickly our research and product teams can iterate.
What You'll DoDesign, build, and operate distributed systems that support large-scale model training and inference across thousands of accelerators
Build and maintain core infrastructure, including orchestration, scheduling, storage, and resource management systems
Improve the reliability, performance, and observability of infrastructure used across research and product teams
Partner with researchers and platform engineers to understand infrastructure needs and turn them into robust, well-abstracted systems
Debug and resolve complex distributed failures across the stack, from networking and storage to compute and scheduling
Write and maintain internal libraries and APIs, primarily in Python and Go, that other engineers build on
Minimum Qualifications
Demonstrated expertise designing and developing large-scale distributed systems
Strong proficiency in Python and Go
Experience building, deploying, and operating production infrastructure at scale
Solid grounding in distributed systems fundamentals, such as consensus, consistency, fault tolerance, and networking
Preferred Qualifications
Experience with ML infrastructure, such as training orchestration, job schedulers, or distributed storage and data systems
Experience operating large-scale GPU or TPU clusters
Experience with container orchestration (e.g. Kubernetes) and infrastructure-as-code
Contributions to open-source infrastructure projects
Comfortable working with high autonomy in a fast-changing, early-stage environment
Location: This role is based in San Francisco, CA.
Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $400,000 USD.
Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.
How we rate this
Software Engineer, Infrastructure at Thinking Machines Lab rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where cluster management was part of your work. What did you do?
- Tell me about a project where ml infrastructure was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Distributed Systems, Infrastructure, Cluster Management, ML Infrastructure, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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